{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "f21524b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "# 参数定义\n",
    "part1_cost = 4\n",
    "part2_cost = 18\n",
    "assemble_cost = 6\n",
    "detect_cost_part1 = [2, 2, 2, 1, 8, 2]\n",
    "detect_cost_part2 = [3, 3, 3, 1, 1, 3]\n",
    "detect_cost_final = [3, 3, 3, 2, 2, 3]\n",
    "market_price = 56\n",
    "replace_loss = [6, 6, 30, 30, 10, 10]\n",
    "decompose_cost = [5, 5, 5, 5, 5, 40]\n",
    "\n",
    "# 生产成品数量\n",
    "N = 100\n",
    "# 蒙特卡洛模拟次数\n",
    "simulations = 100\n",
    "\n",
    "# 计算多个成品的销量与利润\n",
    "def compute_total_sales_and_profit(d1, d2, d3, d4, N, situation, part1_defect_rate, part2_defect_rate, final_product_defect_rate):\n",
    "    defect_rate_part1 = part1_defect_rate[situation] if d1 == 0 else 0\n",
    "    defect_rate_part2 = part2_defect_rate[situation] if d2 == 0 else 0\n",
    "    basic_defect_rate = final_product_defect_rate[situation]\n",
    "    product_defect_rate = 1 - (1 - defect_rate_part1) * (1 - defect_rate_part2) * (1 - basic_defect_rate)\n",
    "    \n",
    "    # 计算合格产品数量与销售额\n",
    "    total_sales = N * (1 - product_defect_rate)\n",
    "    total_revenue = total_sales * market_price\n",
    "\n",
    "    # 计算成本\n",
    "    part1_total_cost = N * (part1_cost + (detect_cost_part1[situation] if d1 == 1 else 0))\n",
    "    part2_total_cost = N * (part2_cost + (detect_cost_part2[situation] if d2 == 1 else 0))\n",
    "    assembly_total_cost = N * (assemble_cost + (detect_cost_final[situation] if d3 == 1 else 0))\n",
    "    \n",
    "    # 如果未检测成品且次品，则产生调换损失\n",
    "    replacement_loss = N * product_defect_rate * replace_loss[situation] if d4 == 0 else 0\n",
    "    \n",
    "    # 拆解成本\n",
    "    decompose_total_cost = decompose_cost[situation] if d4 == 1 else 0\n",
    "\n",
    "    # 总成本\n",
    "    total_cost = part1_total_cost + part2_total_cost + assembly_total_cost + replacement_loss + decompose_total_cost\n",
    "    \n",
    "    # 总利润 = 总收入 - 总成本\n",
    "    total_profit = total_revenue - total_cost\n",
    "    \n",
    "    return total_sales, total_profit\n",
    "\n",
    "# 遗传算法的选择、交叉和变异操作\n",
    "def genetic_algorithm_optimization(simulations, generations=10, population_size=10, mutation_rate=0.1):\n",
    "    population = [(np.random.randint(0, 2), np.random.randint(0, 2), \n",
    "                   np.random.randint(0, 2), np.random.randint(0, 2)) for _ in range(population_size)]\n",
    "    \n",
    "    best_strategies = []\n",
    "    best_sales_per_generation = []\n",
    "    best_profit_per_generation = []\n",
    "    avg_profit_per_generation = []\n",
    "    \n",
    "    for generation in range(generations):\n",
    "        sales_for_population = []\n",
    "        total_profit_generation = []\n",
    "        \n",
    "        for strategy in population:\n",
    "            d1, d2, d3, d4 = strategy\n",
    "            total_sales_list = []\n",
    "            total_profit_list = []\n",
    "            for _ in range(simulations):\n",
    "                # 生成上下浮动3%的缺陷率\n",
    "                part1_defect_rate_variation = np.random.uniform(-0.03, 0.03, size=len(part1_defect_rate))\n",
    "                part2_defect_rate_variation = np.random.uniform(-0.03, 0.03, size=len(part2_defect_rate))\n",
    "                final_product_defect_rate_variation = np.random.uniform(-0.03, 0.03, size=len(final_product_defect_rate))\n",
    "                \n",
    "                part1_defect_rate_modified = part1_defect_rate + part1_defect_rate_variation\n",
    "                part2_defect_rate_modified = part2_defect_rate + part2_defect_rate_variation\n",
    "                final_product_defect_rate_modified = final_product_defect_rate + final_product_defect_rate_variation\n",
    "                \n",
    "                situation = np.random.randint(0, len(part1_defect_rate))\n",
    "                total_sales, total_profit = compute_total_sales_and_profit(d1, d2, d3, d4, N, situation, part1_defect_rate_modified, part2_defect_rate_modified, final_product_defect_rate_modified)\n",
    "                total_sales_list.append(total_sales)\n",
    "                total_profit_list.append(total_profit)\n",
    "            avg_sales = np.mean(total_sales_list)\n",
    "            avg_profit = np.mean(total_profit_list)\n",
    "            sales_for_population.append((strategy, avg_sales, avg_profit))\n",
    "            total_profit_generation.append(avg_profit)\n",
    "        \n",
    "        best_strategy, best_sales, best_profit = max(sales_for_population, key=lambda x: x[2])\n",
    "        best_strategies.append(best_strategy)\n",
    "        best_sales_per_generation.append(best_sales)\n",
    "        best_profit_per_generation.append(best_profit)\n",
    "        avg_profit_per_generation.append(np.mean(total_profit_generation))\n",
    "        \n",
    "        sorted_population = sorted(sales_for_population, key=lambda x: x[2], reverse=True)\n",
    "        parent_population = [x[0] for x in sorted_population[:population_size // 2]]\n",
    "        \n",
    "        new_population = []\n",
    "        for _ in range(population_size // 2):\n",
    "            parent1_idx, parent2_idx = np.random.choice(len(parent_population), size=2, replace=False)\n",
    "            parent1 = parent_population[parent1_idx]\n",
    "            parent2 = parent_population[parent2_idx]\n",
    "            \n",
    "            crossover_point = np.random.randint(1, 4)\n",
    "            offspring1 = parent1[:crossover_point] + parent2[crossover_point:]\n",
    "            offspring2 = parent2[:crossover_point] + parent1[crossover_point:]\n",
    "            new_population.extend([offspring1, offspring2])\n",
    "        \n",
    "        for i in range(len(new_population)):\n",
    "            if np.random.rand() < mutation_rate:\n",
    "                mutation_idx = np.random.randint(0, 4)\n",
    "                new_population[i] = list(new_population[i])\n",
    "                new_population[i][mutation_idx] = 1 - new_population[i][mutation_idx]\n",
    "                new_population[i] = tuple(new_population[i])\n",
    "        \n",
    "        population = new_population\n",
    "\n",
    "    return best_strategies, best_sales_per_generation, best_profit_per_generation, avg_profit_per_generation\n",
    "\n",
    "# 启动实验过程\n",
    "best_strategies_all = []\n",
    "best_profit_all = []\n",
    "\n",
    "for exp in range(50):\n",
    "    # 随机生成缺陷率参数\n",
    "    part1_defect_rate = [0.1, 0.2, 0.1, 0.2, 0.1, 0.05]\n",
    "    part2_defect_rate = [0.1, 0.2, 0.1, 0.2, 0.2, 0.05]\n",
    "    final_product_defect_rate = [0.1, 0.2, 0.1, 0.2, 0.1, 0.05]\n",
    "\n",
    "    # 启动遗传算法\n",
    "    best_strategies, _, best_profit_per_generation, _ = genetic_algorithm_optimization(simulations, generations=500, population_size=20, mutation_rate=0.1)\n",
    "    \n",
    "    best_strategies_all.append(best_strategies[-1])\n",
    "    best_profit_all.append(best_profit_per_generation[-1])\n",
    "\n",
    "# 可视化结果\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(range(50), best_profit_all, label='Best Profit per Experiment', marker='o')\n",
    "plt.xlabel('Experiment')\n",
    "plt.ylabel('Profit')\n",
    "plt.title('Best Profit per Experiment')\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c19a6472",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "# 参数定义\n",
    "p = 200  # 成品的市场售价\n",
    "m = 2  # 工序数\n",
    "n = 8  # 零配件数\n",
    "N = 100  # 假设的生产数量\n",
    "\n",
    "# 零配件次品率、成本、检测成本\n",
    "q_ij = [0.1] * n  # 每个零配件的次品率\n",
    "c_ij = [2, 8, 12, 2, 8, 12, 8, 12]  # 零配件的成本\n",
    "d_ij = [1, 1, 2, 1, 1, 2, 1, 2]  # 零配件检测成本\n",
    "\n",
    "# 成品次品率、装配成本、检测成本\n",
    "p_f = 0.1  # 成品次品率\n",
    "c_f = 8  # 成品装配成本\n",
    "d_f = 6  # 成品检测成本\n",
    "r = 40  # 成品调换损失\n",
    "d_c = 10  # 成品拆解成本\n",
    "\n",
    "# 决策变量生成函数（遗传算法种群初始化）\n",
    "def generate_population(size):\n",
    "    population = []\n",
    "    for _ in range(size):\n",
    "        # 每个个体包括 m*n 个零配件的检测决策，1个成品检测决策，1个拆解决策\n",
    "        x_ij = np.random.randint(0, 2, size=(m, n))  # 零配件检测决策\n",
    "        x_f = np.random.randint(0, 2)  # 成品检测决策\n",
    "        x_d = np.random.randint(0, 2)  # 拆解决策\n",
    "        population.append((x_ij, x_f, x_d))\n",
    "    return population\n",
    "\n",
    "# 计算利润和销量的函数\n",
    "def compute_profit_and_sales(x_ij, x_f, x_d, simulations, q_ij, p_f):\n",
    "    total_profits = []\n",
    "    total_sales = []\n",
    "    \n",
    "    for _ in range(simulations):  # 进行多次模拟\n",
    "        total_profit = 0\n",
    "        total_sales_for_simulation = 0\n",
    "        defect_rate = 1  # 初始次品率为 1\n",
    "        \n",
    "        # 零配件阶段利润和次品率计算\n",
    "        for i in range(m):\n",
    "            for j in range(n):\n",
    "                if x_ij[i][j] == 0:\n",
    "                    total_profit -= c_ij[j]  # 不检测，直接产生成本\n",
    "                else:\n",
    "                    # 检测后减少次品率\n",
    "                    total_profit += (1 - q_ij[j]) * (p - c_ij[j] - d_ij[j])\n",
    "                    defect_rate *= (1 - q_ij[j])\n",
    "\n",
    "        # 成品阶段利润计算\n",
    "        if x_f == 0:\n",
    "            total_profit += (1 - p_f) * p - c_f - r  # 不检测\n",
    "            defect_rate *= p_f\n",
    "        else:\n",
    "            total_profit += (1 - p_f) * (p - d_f) - c_f  # 检测后利润\n",
    "            defect_rate *= (1 - p_f)\n",
    "\n",
    "        # 计算合格产品数量（销量）\n",
    "        qualified_products = (1 - defect_rate) * N\n",
    "        total_sales_for_simulation = qualified_products\n",
    "\n",
    "        # 拆解阶段利润计算\n",
    "        if x_d == 0:\n",
    "            total_profit -= d_c  # 不拆解\n",
    "        else:\n",
    "            total_profit += sum([p_j * (p - c_ij[j]) for j, p_j in enumerate(q_ij)])  # 拆解后回收零配件\n",
    "\n",
    "        total_profits.append(total_profit)\n",
    "        total_sales.append(total_sales_for_simulation)\n",
    "\n",
    "    # 返回多次模拟的平均利润和平均销量\n",
    "    avg_profit = np.mean(total_profits)\n",
    "    avg_sales = np.mean(total_sales)\n",
    "    return avg_profit, avg_sales\n",
    "\n",
    "# 遗传算法主流程\n",
    "def genetic_algorithm_optimization(pop_size, generations, simulations, mutation_rate, q_ij, p_f):\n",
    "    # 初始化种群\n",
    "    population = generate_population(pop_size)\n",
    "    best_strategy = None\n",
    "    best_profit = -np.inf\n",
    "    \n",
    "    for generation in range(generations):\n",
    "        profits = []\n",
    "        \n",
    "        # 计算每个个体的平均利润和销量（蒙特卡洛模拟）\n",
    "        for individual in population:\n",
    "            x_ij, x_f, x_d = individual\n",
    "            profit, sales = compute_profit_and_sales(x_ij, x_f, x_d, simulations, q_ij, p_f)\n",
    "            profits.append((individual, profit))\n",
    "        \n",
    "        # 找到当前种群中利润最高的个体\n",
    "        current_best_individual, current_best_profit = max(profits, key=lambda x: x[1])\n",
    "\n",
    "        # 更新最优个体\n",
    "        if current_best_profit > best_profit:\n",
    "            best_strategy = current_best_individual\n",
    "            best_profit = current_best_profit\n",
    "\n",
    "        # 选择过程\n",
    "        sorted_population = sorted(profits, key=lambda x: x[1], reverse=True)\n",
    "        parent_population = [x[0] for x in sorted_population[:pop_size // 2]]\n",
    "\n",
    "        # 交叉生成后代\n",
    "        new_population = []\n",
    "        for _ in range(pop_size // 2):\n",
    "            parent1, parent2 = np.random.choice(len(parent_population), size=2, replace=False)\n",
    "            parent1 = parent_population[parent1]\n",
    "            parent2 = parent_population[parent2]\n",
    "            \n",
    "            # 交叉点的选择\n",
    "            crossover_point = np.random.randint(1, n)\n",
    "            offspring1_x_ij = np.vstack((parent1[0][:crossover_point], parent2[0][crossover_point:]))\n",
    "            offspring2_x_ij = np.vstack((parent2[0][:crossover_point], parent1[0][crossover_point:]))\n",
    "\n",
    "            offspring1 = (offspring1_x_ij, parent1[1], parent1[2])\n",
    "            offspring2 = (offspring2_x_ij, parent2[1], parent2[2])\n",
    "            new_population.extend([offspring1, offspring2])\n",
    "\n",
    "        # 变异过程\n",
    "        for i in range(len(new_population)):\n",
    "            if np.random.rand() < mutation_rate:\n",
    "                mutation_idx = np.random.randint(0, n)\n",
    "                new_population[i][0][0][mutation_idx] = 1 - new_population[i][0][0][mutation_idx]  # 变异\n",
    "\n",
    "        population = new_population\n",
    "\n",
    "    return best_strategy, best_profit\n",
    "\n",
    "# 进行50次变化\n",
    "profits = []\n",
    "strategies = []\n",
    "\n",
    "for _ in range(50):\n",
    "    # 随机浮动零配件次品率和成品次品率\n",
    "    fluctuated_q_ij = [q + np.random.uniform(-0.03, 0.03) for q in q_ij]\n",
    "    fluctuated_p_f = p_f + np.random.uniform(-0.03, 0.03)\n",
    "\n",
    "    # 优化\n",
    "    best_strategy, best_profit = genetic_algorithm_optimization(\n",
    "        pop_size=10,  # 种群大小\n",
    "        generations=500,  # 迭代次数\n",
    "        simulations=100,  # 蒙特卡洛模拟次数\n",
    "        mutation_rate=0.1,  # 变异率\n",
    "        q_ij=fluctuated_q_ij,\n",
    "        p_f=fluctuated_p_f\n",
    "    )\n",
    "    \n",
    "    profits.append(best_profit)\n",
    "    strategies.append(best_strategy)\n",
    "\n",
    "# 绘制利润变化图\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(profits, label='Profits')\n",
    "plt.xlabel('Iteration')\n",
    "plt.ylabel('Profit')\n",
    "plt.title('Profit Over 50 Iterations with Varying Defect Rates')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e5d31855",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
